Petroleum Research最新文献

Geomechanical properties have a prominent influence on reservoir stresses, which consequently reduce permeability and porosity with pressure depletion. These properties significantly affect the accuracy of reservoir modeling and recovery calculation, but have not been fully studied; therefore, more work is needed. Full field data and laboratory measurements are included in the study. The work involves deriving an equation by combining experimental data for permeability and porosity reduction during a change in stress with the poroelastic stress equation to investigate the impact of Poisson's ratio and Young's modulus on the reduction of permeability and porosity with pressure depletion. Most simulation studies assume constant geomechanical properties across the entire reservoir or for each individual reservoir layer. In this study, three approaches were considered for the Poisson's ratio and Young's modulus in the reservoir model: 1) constant average values assigned to the entire reservoir, 2) constant average values assigned to each layer, and 3) constant values assigned to each grid block. The validity of the model results was checked by history matching with production and pressure data. For the studied tight reservoir, the Poisson's ratio and Young's modulus significantly affected the permeability and porosity reduction with pressure depletion. The impact of Young's modulus was more pronounced than Poisson's ratio. The simulation results for oil rate, cumulative oil production, and water cut for the reservoir and a selected well showed that applying the three suggested geomechanical approaches resulted in a substantial discrepancy in the model outcome. In general, the coupled model with the mapped geomechanical properties resulted in lower oil and water production. This is attributed to the large values of mapped Young's modulus in parts of the reservoir which resulted in large permeability reduction and subsequently lower oil and water production is expected. In contrast lower Young's modulus per layer was obtained due to averaging process. Poisson's ratio effect on fluid production is much less significant due to its small effect on permeability reduction with depletion. Similarly, the adoption of different geomechanical property values for each layer yielded a relatively lower production outcome than when using a constant value for the entire reservoir. The study indicates the importance of considering the detailed description of the reservoir geomechanical properties to obtain reliable simulation results.

Various uncertainty quantification methodologies are presented using a combination of several deterministic decline curve analysis models and two bootstrapping algorithms. These probabilistic models are applied to 126 sample wells from the Permian basin. Results are presented for 12–72 months of production hindcast given an average well production history of 103 months. Based on the coverage rate and the forecast error (with the coverage rate being more significant in our choice of the best probabilistic models) and using up to one-half of the available production history for a group of sample wells from the Permian Basin, we find that the CBM-SEPD combination is the best probabilistic model for the Central Basin Platform, the MBM-Arps combination is the best probabilistic model for the Delaware Basin, the CBM-Arps is the best probabilistic model for the Midland Basin, and the best probabilistic model for the overall Permian Basin is the CBM-Arps when early time data is used as hindcast and CBM-SEPD for when one-quarter to one-half of the data is used as hindcast. When three-quarters or more of the available production history is used for analysis, the MBM-SEPD probabilistic model is the best combination in terms of both coverage rate and forecast error for all the sub-basins in the Permian. The novelty of this work lies in its extension of bootstrapping methods to other decline curve analysis models. This work also offers the engineer guidance on the best choice of probabilistic model whilst attempting to forecast production from the Permian Basin.

Carbonate rocks exhibit complex and heterogeneous pore structures; such heterogeneity is manifested by the occurrence of a wide variety of pore types with different sizes and geometries as a result of depositional and diagenetic processes. These complications substantially increase the uncertainty of predicted rock hydraulic parameters because samples with comparable porosities might have very different permeability values. In this study, small-scale characterisation of porosity and permeability in heterogeneous Eocene limestone samples from the Bassein Formation of the B-X structure of the MK Field in Mumbai Offshore Basin, India, was carried out, employing an integrated framework that incorporates thin-section petrography, routine core analysis, mercury injection capillary pressure and nuclear magnetic resonance data. The pore characteristics of these carbonates range from poor to excellent. The studied samples exhibited large ranges of porosity, permeability and other associated petrophysical attributes. The pore types, as well as their orientations and connectivity, are the primary factors causing the heterogeneity. Because of the complexity of the pore networks, a simple lithofacies classification alone would have been insufficient to link porosity and permeability. The reservoir characteristics in the study area are strongly linked to the development and/or destruction of reservoir porosity–permeability during different phases of diagenesis. Twenty-four carbonate core samples from the limestone unit were studied and classified into microfacies and pore type classes, producing an accurate assessment of reservoir attributes. The comprehensive workflow incorporates the pore volume distributions and pore throat attributes for each rock type. Three carbonate microfacies were identified by petrographic analysis and their petrophysical characteristics, such as porosity, permeability, pore throat size, pore volume and fluid flow factors, were measured. The study demonstrates how macroporosity, mesoporosity and microporosity are associated with various rock types and how they affect permeability and cementation exponents. The results of this study provide a comprehensive experimental framework for geological and geophysical interpretation that can be applied to identify potential reservoir facies and strengthen our understanding of heterogeneous carbonates. The framework can also be used to guide reservoir evaluation of similar heterogeneous formations in other areas.

Drilling mud is a major concerning element due to its high operational and economic impact on the drilling process. Various additives are introduced to enhance the efficiency of drilling fluid, but none of them could perfectly achieve their proposed efficacy in drilling operations. Researchers conceived several nanoparticles (NPs) in drilling fluid to dissolve this issue. In a singular instance, commercial tin oxide (SnO₂) nanoparticles were utilized to analyze the influence of NPs on the rheological and filtration properties of inorganic KCl salt-based drilling fluid. However, the effect of SnO₂ NPs on mud lubricity characteristics is not studied previously. However, due to the hazardous behavior of KCl, its use is very limited. Thus, we consider a KCl-free bentonite water-based mud to avoid any environmental damages from drilling operations. We also use SnO₂ NPs that is synthesized in our laboratory by co-precipitation method. In addition to rheological and filtration properties, we also investigate the effect of NPs on mud's lubricity that was not considered in the previous study. Drilling fluid properties are measured at five different NPs concentrations of 0.10, 0.25, 0.50, 0.75 & 1.0 wt%, and at six different temperatures of 30, 40, 50, 60, 70, and 80 °C, while filtration properties are measured using API low-pressure low temperature (LPLT) condition. The addition of 0.1 wt% SnO₂ NPs increases plastic viscosity, yield point, 10 s gel strength, and 10 min gel strength by 10%, 63%, 20%, and 14%, respectively. The maximum reduction in lubricity coefficient is found to be 14% at NPs concentration of 1.0 wt%. The NPs concentration of 0.5 wt% yielded a reduction in fluid loss and mud cake thickness by 8.1% and 34%, respectively. The study suggests that SnO₂ NPs can be employed as an additive to improve the rheology, lubricity, and filtration properties of KCl-free bentonite water-based drilling mud.

Geographic traceability is crucial to global oil trade security. This study discusses the possibility of using multivariate statistical methods combined with multi-indicator analysis to identify samples of crude oil imports from five major countries to China. The physicochemical properties and trace elements of crude oil were detected by Petroleum product standards and inductively coupled plasma atomic emission spectrometry (ICP-AES). Eight indexes (moisture, density, sulfur content, acid value, organochlorine, carbon residual, V, and Ni) were analyzed. Principal component analysis (PCA), hierarchical clustering analysis (HCA), Orthogonal projections to lateen structures-discriminant analysis (OPLS-DA), and other multivariate data analysis methods were used to determine the geographical origin of crude oil samples. Satisfying results have been obtained using PCA to reduce the dimensions of the indicators of crude oil from different origins. It allows the reduction of 8 variables to 3 principal components and accounts for 80.06% of the total variance. The HCA shows five clusters corresponding to five sources of crude oil. This will help to improve the utilization rate of crude oil with different characteristics, improve the quality of crude oil trade, and ensure the high quality of crude oil trade. For the sample set used for modeling, the model's accuracy was 97.19% after OPLS-DA optimization. These results show that the combination of multi-index analysis and stoichiometry is an effective tool for identifying crude oil origin, which fills the technical gap in the rapid identification of crude oil origin.

Steam injection is commonly used for production of viscous crude oil. Reservoir rock often contains clay minerals. Reactive nature of steam and clay minerals may lead to formation damage. This work investigates oil recovery and changes in petrophysical properties as a function of the mineralogy. Sandpacks with quartz, calcite, feldspar, kaolinite, smectite, and illite were prepared for steam injection experiments. Permeability of the steamed sandpacks was determined using coreflood experiments. Chemical composition of the produced aqueous samples was determined using ICP-OES (inductively coupled plasma-optical emission spectroscopy). Morphology of the rock samples was studied using SEM-EDS (scanning electron microscope-energy dispersive X-ray spectroscopy). Mineralogy and elemental content of the solid samples were determined using XRD (X-ray diffraction) analysis and XRF (X-ray fluorescence) respectively. It was found that aqueous phase samples produced from clay-rich sandpacks tend to have higher pH than samples produced from samples without clay minerals. Oil recovery factors for 100% quartz case was determined to be 65 wt%. Calcite- and feldspar-rich sandpacks produced 56 and 61 wt% of oil respectively. Sandpacks with clay fractions have shown the lowest oil recovery – 39, 29, and 28 wt% for kaolinite-, smectite-, and illite-rich samples respectively. Mineral dissolution and precipitation were the dominant damaging mechanism for quartz and calcite cases. Feldspar-rich sandpack demonstrated signs of structural destruction of the mineral and fines release. Kaolinite's effect on oil recovery was found to be associated with fines migration. Smectite hydration and swelling in presence of steam was the dominant formation damage effect on the oil production. Steam interaction with illite-rich sandpack caused formation of amorphous silica. This paper presents oil recovery factors as a function of injected pore volume (PV) of steam for sandpacks of different mineralogy. Obtained results characterize petrophysical changes caused by steam interaction with minerals in presence of oil. This data provides insights into effects of steam on minerals with different structures and properties.

The jet pump is an artificial lift employed when the reservoir pressure declines and the well deviation increases. The use of computer well models for optimizing the oil well output has proven to be a successful strategy, and has helped increasing the efficiency and production of numerous wells. The objective of this study was to use a production optimization technique that achieves some improvements, and recommend approaches toward increasing the oil well production. The effects of the motive fluid flow rate and pressure on the oil production rate were investigated to determine the optimal injection rate and pressure on the performance of the deep well water-oil axial jet-pump. Additionally, the effects of the well-head pressure, water cut, and roughness of tubing on oil production of this jet pump type were investigated. The results revealed that the impact on the oil lift performance is significant. The oil production increased by 19.43%, and the optimal economic value for the injection rate and pressure for the GA-1A well are 744.44 BFPD and 2722.22 psig, respectively. In summary, increasing the tubing roughness decreased the well's total liquid production. Thus, maintaining the well integrity is a very important factor because not doing so can lower the productivity by up to 20%–25%.

Regular inspection of long-distance oil and gas pipelines plays an important role in ensuring the safe transportation of oil and gas, and inspection on welding defects is an important part of the inspection process. Magnetic flux leakage (MFL) is an electromagnetic non-destructive testing technique which has been commonly utilized to detect welding defects in pipelines. In the present study, Maxwell electromagnetic simulation software was used to carry out numerical study on the welding defects in pipelines, including incomplete penetration and undercut. The Ф406 pipeline with a wall thickness of 7 mm was selected as the study case to establish the numerical model. Setting the life-off value at 1 mm, the distribution of magnetic leakage field was investigated for pipeline without defect, pipeline with incomplete penetration defect and pipeline with undercut defect respectively, the characteristic values describing the depth and width of defects were found. Furthermore, quantified equations which can be used to describe the defect depth were proposed. Finally, experimental research was carried out to validate the effectiveness of the numerical model, and the experimental results showed good consistence with the numerical calculation results. The research results indicate that, it is technically feasible and reliable to diagnose the incomplete penetration and undercut welding defects in pipelines using MFL.

Enhanced oil recovery by CO₂ injection technology (CO₂-EOR) plays a crucial role in enhancing oil production and the permanent sequestration of anthropogenic CO₂ in depleted oil reservoirs. However, the availability of CO₂ in oil field locations and its mobility in contrast with reservoir fluids are prime challenges in CO₂-EOR. The cost of CO₂ and its availability at the oil fields has prompted investigations on efficient injection of CO₂ at the fields to achieve the best sweep efficiency possible. Injection strategies such as water-alternating-gas (WAG), simultaneous vertical and horizontal WAG, simultaneous water injection into the aquifer and vertical WAG, water and gas injection simultaneously but separately (SS-WAG), and water and gas injection simultaneously but not separately (SNS-WAG) play a significant role, as well as the purity of CO₂. In this work, the significance of the above criteria was investigated individually and in combination. The coupled sequence of injection rate, soaking time, WAG ratio, and purity of injected CO₂ for enhancement of oil production were delineated. A realistic reservoir simulation model conceptualizing the CO₂-EOR system with five spot injection patterns was developed by the company CMG. The history-matched model that was developed was used to investigate the sensitivity of the coupled effects to the criteria listed above on oil recovery. Numerical investigations quantitatively emphasized that purity and soaking time of CO₂ have an inverse effect in the oil production rate and that SNS-WAG resulted in a better oil production rate than SS-WAG.

The present study aims to integrate a large set of geological and geophysical data into a comprehensive model describing the depositional features of the Abu Madi/El Qar'a/Khilala gas fields. The model is based on the sequence stratigraphic framework of the Abu Madi Formation defined using cores, well logs, and time-migrated seismic data. Seismic trace attribute sections and relative acoustic impedance sections are also used. A possible depositional pattern for the main Level III is established, based on the lithological and petrophysical information derived from the seismic data analysis. The Abu Madi Formation can be regarded as a depositional sequence recording the progressive drowning of the incised valley. The sequence is bounded at the base by an erosional unconformity, created by a drop in the level of the Late Messinian Sea, and at the top by a drowning unconformity related to the Early Pliocene transgression. The bottom of Level II divides the Abu Madi sequence into two smaller sequences. In both sequences, gas-bearing traps can be found in the Lowstand Systems Tracts, represented by the fluvial Level III and fluvial-deltaic Level II, respectively.